---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-base-uncased-finetuned-switchboard-2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilbert-base-uncased-finetuned-switchboard-2

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the validation set:
- Loss: 0.7090
- Accuracy: 0.7215
- Precision: 0.7176
- Recall: 0.7215
- F1: 0.7188

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2139        | 1.0   | 370  | 0.8510          | 0.6875   | 0.6831    | 0.6875 | 0.6846 |
| 0.3195        | 2.0   | 740  | 0.7090          | 0.7215   | 0.7176    | 0.7215 | 0.7188 |


### Framework versions

- Transformers 4.13.0
- Pytorch 1.13.0+cu116
- Datasets 1.16.1
- Tokenizers 0.10.3